Time-series data has traditionally been stored as raw data or as rows of a relational database. Handling, reading and manipulation can then be extremely cumbersome, and in the relational database case, inefficient.
A related IBM technology is Aggregated Database (ADB). ADB is a method to store time-series which essentially works by dividing the time axis into blocks which are treated independently. The average of the signal over each block is obtained and stored in an array. While it has proven so far extremely useful for AURORA (particularly it is extremely fast), it has certain disadvantages, which include: It requires multiple databases to deal with different accuracy requirements depending on the time-scale (hour, day, month, year, etc.) The lossy compression space/accuracy tradeoff performance is not good. The artificial partitioning of the time axis induces block effects (i.e. lack of smooth transitions) and does not permit exploitation of compression across blocks.
One popular method for storing time-series information is the freely available Round-Robin Database (RRD). It creates fixed-size databases with data arrays of predetermined lengths, where multiple arrays are used to record samples of multiple variables or parameters. RRD circularly fills these arrays, such that only the most recent data samples are held, corresponding to a sliding window of the parameter time series. It can only be thought of as imposing degraded accuracy as a function of time in the extreme values outside of the circular buffer are lost. Disadvantages of RRD include that data arrays consume disk space for all potential aggregation data values, even if the data arrays are filled only sparsely and values are inserted for a specific point in time, despite the fact that, for many data measurement applications, the primary measurement data is concentrated over an interval and not at one specific instance.
The IBM InformixR® TimeSeries DataBlade™ module is an add-on for the IBM relational database Informix for the management of time-series and temporal data. It enables simplification in coding and permits complex queries. The time-series values are stored as a single row in a relational databases table. The traditional way is to store each (time-stamp, value) pair as one row. What is referred to as a calendar is used to encode the timestamps. There is also an associated IBM Informix-NAG Financial DataBlade module add-on that uses the well-known numerical analysis library NAG to perform complex calculations on TimeSeries data. The Informix TimeSeries DataBlade is a more natural way to store time-series data than the traditional relational method. However, this module boils down to an embedding of the data within the database, together with a framework to manipulate it. Neither compression nor a time/accuracy tradeoff appear to be offered, as options.